Abstract/Summary

Determining the distribution and abundance of life is challenging, especially in the deep sea where high pressure and other logistical challenges limit data availability to a tiny fraction of what is available for other systems. Most of Earth’s surface is nonetheless covered by water > 2000 m deep. Life in these abyssal regions influences the burial of carbon and nutrient cycling. Long-term research has now shown that even larger animals in the deep sea can vary in density by orders of magnitude, with concurrent changes in average body size, over periods as short as months. These variations are widely believed to be linked to climate-driven variation in the food supply to the deep sea. Similarly, biogeography studies have found that over distances approaching 100 km or more, the abundance of deep-sea life is related to surface productivity in the waters above. Thus the deep sea could be readily impacted by processes that alter surface ocean conditions like climate change, fishery activity, or ocean iron fertilisation.
While there has been an increase in the understanding of how climate and surface processes affect deep-sea communities, the ability to understand these links further is thought to be limited by sampling error from undetected habitat heterogeneity (i.e. irregular or uneven habitat distributions). Features like hills, valleys, depressions, small rock outcrops, and biogenic mounds add to habitat complexity, but links between such features and the animals that live among them are very poorly resolved in abyssal plain habitats using current methods. We proposed a new approach using the autonomous underwater vehicle (AUV) Autosub6000 to survey ecologically the Porcupine Abyssal Plain (PAP) Sustained Observatory to address a key question: Are spatial patterns in abyssal habitat features (like bathymetry, seafloor cover of phytodetrius [i.e. food availability], suspended solid concentration) related to spatial patterns in photographed life (density, dispersion, or biodiversity) at spatial scales from <1 m^2 to about 100 km^2?
Objectives
1. We created high-resolution ecological maps at scales of <1 m^2 to 100 km^2.
2. We will then test tractable hypotheses focusing on if any observed faunal distributions are linked with the spatial patterns of other fauna, habitat, food availability, or environmental conditions.
3. We will use the results to improve estimates of deep-sea biodiversity and ecosystem function of megafauna and relate the findings to factors such as food availability.
4. We will enhance UK capability in evaluating abyssal ecology and facilitate future time-series ecological research surveys.
Activities
• Crude oil spill impact experiments
• CTD rosette-based prokaryotic sampling.
• Megacoring
• Box coring
• Seabed High Resolution Imaging Platform (SHRIMP) surveys
• Autosub6000 surveys including acoustic mapping and photography